Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: State of the art and challenges
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Published
Nov 11, 2025
Trung-Thanh N. Thai
Phuc Do
Benoit Iung Paolo Gardoni
https://orcid.org/0000-0003-4113-5895
Benoit Iung Paolo Gardoni
Abstract
Prognostics and maintenance decision-making rely heavily on accurate and reliable measurements derived from sensors. However, sensor degradation introduces measurement uncertainties that compromise the precision of fault detection, remaining useful life estimation, and overall maintenance strategies. This paper provides a comprehensive review of the multifaceted impacts of sensor degradation on measurement uncertainty and its subsequent influence on prognostics and maintenance. The paper synthesizes various sensor degradation mechanisms and existing modelling techniques, emphasizing the growing research focus on developing accurate degradation models. The review also provides an in-depth analysis of how sensor degradation affects measurement uncertainty, exploring both qualitative and quantitative impacts through various modelling approaches and tools. Furthermore, this review examines the implications of this uncertainty on prognostics and maintenance decision-making methodologies, showcasing current mitigation methods and models. Finally, the review identifies key challenges and research gaps, outlining promising directions for future research in sensor degradation and its impact on prognostics and maintenance. By addressing these critical issues, this paper contributes to the advancement of more reliable, adaptive, and efficient Prognostics and Health Management (PHM) systems across various industrial and technological domains.
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Keywords
Sensor Degradation, Measurement Uncertainty, Prognostics, Maintenance Decision-Making
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